Control your Android devices with AI using Model Context Protocol
DroidMind is a powerful bridge between AI assistants and Android devices, enabling control, debugging, and system analysis through natural language. By implementing the Model Context Protocol (MCP), DroidMind allows AI models to directly interact with Android devices via ADB in a secure, structured way. When used as part of an agentic coding workflow, DroidMind can enable your assistant to build and debug with your device directly in the loop.
DroidMind empowers AI assistants to:
For a detailed list of capabilities, see the User Manual and MCP Reference.
uvx
)For the fastest way to integrate DroidMind with an MCP-compatible IDE (like Cursor), you can configure it to run DroidMind directly from its GitHub repository using uvx
. This method does not require you to manually clone or install DroidMind first.
Add the following to your IDE's MCP configuration (e.g., .cursor/mcp.json
for Cursor):
{
"mcpServers": {
"droidmind": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/hyperb1iss/droidmind",
"droidmind",
"--transport",
"stdio" // The default and preferred mode for most IDE integrations
]
}
}
}
Your IDE will be configured to launch DroidMind on demand. Full instructions for this setup are in the Quick Start Guide.
uv
(Python package manager)For detailed instructions on setting up DroidMind, including the quick IDE integration with uvx
(covered in the Quick Start), manual installation from source, or using Docker, please see our comprehensive Installation Guide.
How you run DroidMind depends on your setup:
uvx
): Your IDE automatically manages running DroidMind as configured in its MCP settings (e.g., mcp.json
). See the Quick Start Guide.droidmind --transport stdio
droidmind --transport sse
This usually starts a server at sse://localhost:4256/sse
.Refer to the Installation Guide for more details on running DroidMind in different environments.
DroidMind can also be run using Docker for a consistent, containerized environment. This is particularly useful for deployment and isolating dependencies.
For comprehensive instructions on building the Docker image and running DroidMind in a container with stdio
or SSE
transport, including notes on ADB device access, please refer to our Docker Guide.
With an AI assistant connected to DroidMind, you can make requests like:
emulator-5554
."your_device_serial
."emulator-5554
."For more inspiration, check out our Example Queries and Workflows in the User Manual.
DroidMind incorporates a security framework to protect your devices:
High-risk operations are flagged, and critical ones are blocked by default. Learn more in our Security Considerations chapter.
DroidMind uses uv
for dependency management and development workflows.
# Install/update dependencies (after cloning and activating .venv)
uv pip install -e .[dev,sse]
# Run tests
pytest
# Run linting
ruff check .
# Run type checking
pyright # Ensure pyright is installed or use ruff's type checking capabilities
Contributions are welcome! Please feel free to submit a Pull Request.
git checkout -b feature/amazing-feature
).uv
.git commit -m 'Add some amazing feature'
).git push origin feature/amazing-feature
).This project is licensed under the Apache License - see the LICENSE file for details.
Created by Stefanie Jane 🌠
If you find DroidMind useful, buy me a Monster Ultra Violet ⚡️
{ "mcpServers": { "droidmind": { "command": "uvx", "args": [ "--from", "git+https://github.com/hyperb1iss/droidmind", "droidmind", "--transport", "stdio" ] } } }
Related projects feature coming soon
Will recommend related projects based on sub-categories